• DocumentCode
    560712
  • Title

    Computational intelligence technique based PI controller using SVC

  • Author

    Kamari, Nor Azwan Mohamed ; Musirin, Ismail ; Othman, Muhammad Murtadha

  • Author_Institution
    Fac. of Electr. Eng., Univ. Teknol. Mara, Shah Alam, Malaysia
  • Volume
    2
  • fYear
    2011
  • fDate
    8-9 Sept. 2011
  • Firstpage
    354
  • Lastpage
    357
  • Abstract
    This paper presents Evolutionary Programming (EP) based optimization technique for estimating PI controller parameters of a Static Var Compensator (SVC) which controls a synchronous machine. SVC is one type of Flexible AC Transmission Systems (FACTS) device, designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. Computational intelligence technique based PI controller using SVC is implemented in this study. The study involves the development of PI controller for SVC placement, while computational intelligence technique is used to optimize the values of proportional gain, KP and interval gain, KI parameters of PI controller. Validation with respect to eigenvalues determination and synchronizing and damping torque coefficients (KS and KD) value confirmed that the proposed technique is effective to improve the angle stability problem.
  • Keywords
    PI control; flexible AC transmission systems; machine control; static VAr compensators; synchronous generators; FACTS; PI controller; SVC; computational intelligence technique; evolutionary programming based optimization technique; flexible AC transmission systems; static VAr compensator; synchronous generator; synchronous machine; system voltage control; Damping; Mathematical model; Power system stability; Programming; Rotors; Static VAr compensators; Torque; Damping Torque Coefficient; Evolutionary Programming; Synchronizing Torque Coefficient; Transient Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Automation Conference (PEAM), 2011 IEEE
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9691-4
  • Type

    conf

  • DOI
    10.1109/PEAM.2011.6134959
  • Filename
    6134959